Comparing SARS-CoV-2 Viral Load in Human Saliva to Oropharyngeal Swabs, Nasopharyngeal Swabs, and Sputum: A Systematic Review and Meta-Analysis

A systematic review and meta-analysis were conducted to investigate the SARS-CoV-2 viral load in human saliva and compared it with the loads in oropharyngeal swabs, nasopharyngeal swabs, and sputum. In addition, the salivary viral loads of symptomatic and asymptomatic COVID-19 patients were compared. Searches were conducted using four electronic databases: PubMed, Embase, Scopus, and Web of Science, for studies published on SARS-CoV-2 loads expressed by CT values or copies/mL RNA. Three reviewers evaluated the included studies to confirm eligibility and assessed the risk of bias. A total of 37 studies were included. Mean CT values in saliva ranged from 21.5 to 39.6 and mean copies/mL RNA ranged from 1.91 × 101 to 6.98 × 1011. Meta-analysis revealed no significant differences in SARS-CoV-2 load in saliva compared to oropharyngeal swabs, nasopharyngeal swabs, and sputum. In addition, no significant differences were observed in the salivary viral load of symptomatic and asymptomatic COVID-19 patients. We conclude that saliva specimen can be used as an alternative for SARS-CoV-2 detection in oropharyngeal swabs, nasopharyngeal swabs, and sputum.


Introduction
Coronavirus disease 2019 , caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), was confrmed as an outbreak reported in Wuhan, China, in December 2019 [1]. Already by March 11th, 2020, it was declared as a global pandemic, indicating the contagiousness and related fast spreading of the virus. By March 16th, 2022, the virus had globally infected over 462 million people with approximately 6 million deaths [2]. To date, these numbers are still increasing.
Most individuals who become infected show mild to moderate fu-like symptoms and recover without hospitalization. Clinical symptoms of COVID-19 are diverse ranging from mild to severe including fever, dry cough, smell-and taste-loss, dyspnea, muscle pain, headache, and respiratory tract infection. In most severe cases, it may lead to lung failure, hospitalization, and death [3]. However, it has been shown that 24% of the population infected with SARS-CoV-2 remained asymptomatic [4,5]. Several risk factors relate to interindividual diferences in sensitivity to COVID-19 including age (fatality rate of patients in the age group 70-80 years is 8% higher than the age groups below [6,7], gender (higher mortality in males) [8,9], genetic factors, and underlying comorbidities (cardiovascular diseases, diabetes mellitus, hypertension, chronic kidney disease, and chronic lung diseases) [6]. Diferences in viral load kinetics in various body fuids may play a role as well [10][11][12][13][14][15].
Te main human-to-human transmission of SARS-CoV-2 occurs via inhalation of aerosols, generated through coughing, sneezing, or direct contact with mucous membranes of the eyes, mouth, and nose [3,[16][17][18][19][20][21][22][23][24][25]. Te receptor-binding domain (RBD) of the coronavirus spike (S) glycoprotein, located on the surface of the viral envelope, mediates viral entry into host cells by binding to the ACE2 (angiotensin-converting enzyme 2) receptor. Te binding of the S-protein to ACE2 is subsequently primed by a host cell protease, TMPRSS2 (transmembrane protease, serine 2), which facilitates cell entry [20][21][22]. High expressions of ACE2 and TMPRSS2 are found in the epithelial cells and human acinar granular cells of the salivary glands [22][23][24][25][26]. In line, the salivary glands may serve as a reservoir of the virus facilitating viral replication and shedding of infectious particles into saliva. Te viral load profle of SARS-CoV-2 in saliva seems to peak during the frst week of symptoms onset [27]. However, the virus may still be detected in low amounts such as approximately ∼2 log10 copies/mL after 20-30 days in saliva, despite the range of salivary antiviral molecules which potentially contribute to counteract the viral load and transmission [1,13,14,[27][28][29][30].
Te collection of respiratory tract secretions such as nasopharyngeal swabs (NPS), oropharyngeal swabs (OPS), and sputum followed by detection of viral genome with RT-PCR has become the gold standard for SARS-CoV-2 screening and diagnosis. However, collection of these matrices has a series of drawbacks regarding discomfort of patients, risk of exposure to healthcare workers, need for specifc instruments, and limiting self-collection [31]. In turn, saliva has been regarded to be an attractive matrix for sampling compared to NPS and OPS collection because it ofers benefts such as noninvasive and quick and easy sampling with minimum risk of exposure to healthcare workers and decreasing the need of personal protective equipment [11][12][13][14][15][32][33][34].
Based on the abovementioned, we hypothesized that SARS-CoV-2 screening and diagnostics in saliva is a good alternative for NPS, OPS, and sputum. It appears, so far, that studies have investigated the detection of SARS-CoV-2 viral loads in saliva specimens indicated in measures of sensitivity and specifcity. However, until now, no studies with metaanalysis have compared the SARS-CoV-2 viral load in saliva to other biofuids expressed in C T values and copies/mL RNA. Terefore, the aim of this systematic review was frst to address the SARS-CoV-2 load (expressed in cycle threshold (C t )-value or copies/mL RNA) in human saliva, and secondly, to compare the viral load in saliva with OPS, NPS, and sputum. Furthermore, the SARS-CoV-2 load in saliva samples of symptomatic and asymptomatic COVID-19 patients was compared. A meta-analysis was conducted to systematically compare the viral load data from diferent studies.

Search
Strategy and Data Sources. Advanced literature search strategy was applied using four electronic databases including PubMed, Embase, Scopus, and Web of Science. Te search strategy was conducted using the combinations of the following key words: (COVID-19 (title/abstract)) OR (coronavirus (title/abstract)) OR (SARS-CoV-2 (title/abstract)) OR (2019-ncov (title/abstract)) AND (saliva (title/ abstract)) OR (saliv * (title/abstract)) OR (salivary (title/ abstract)) OR (oral (title/abstract)) OR (mouth (title/abstract)) OR (oropharynx (title/abstract)) AND (viral load (title/abstract)). A manual search was conducted in order to include other relevant articles. Te search strategy was performed monthly up until April 2021.  Provide an explicit statement of the question(s) the review will address with reference to participants, interventions, comparators, and outcomes (PICO) Methods

Eligibility criteria 8
Specify the study characteristics (e.g., PICO, study design, setting, and time frame) and report characteristics (e.g., years considered, language, and publication status) to be used as criteria for eligibility for the review

Information sources 9
Describe all intended information sources (e.g., electronic databases, contact with study authors, trial registers, or other grey literature sources) with planned dates of coverage Search strategy 10 Present draft of search strategy to be used for at least one electronic database, including planned limits, such that it could be repeated Study records Data management 11a Describe the mechanism(s) that will be used to manage records and data throughout the review

Selection process 11b
State the process that will be used for selecting studies (e.g., two independent reviewers) through each phase of the review (i.e., screening, eligibility, and inclusion in meta-analysis)

Data collection process 11c
Describe the planned method of extracting data from reports (e.g., piloting forms, done independently, and in duplicate), any processes for obtaining and confrming data from investigators Data items 12 List and defne all variables for which data will be sought (e.g., PICO items and funding sources), any preplanned data assumptions and simplifcations Outcomes and prioritization 13 List and defne all outcomes for which data will be sought, including prioritization of main and additional outcomes, with rationale

Risk of bias in individual studies 14
Describe anticipated methods for assessing risk of bias of individual studies, including whether this will be done at the outcome or study level, or both; state how this information will be used in data synthesis Data Synthesis 15a Describe criteria under which study data will be quantitatively synthesized 15b If data are appropriate for quantitative synthesis, describe planned summary measures, methods of handling data, and methods of combining data from studies, including any planned exploration of consistency (e.g., I 2 and Kendall's tau) 15c Describe any proposed additional analyses (e.g., sensitivity or subgroup analysis and meta-regression) 15d If quantitative synthesis is not appropriate, describe the type of summary planned Metabias(es) 16 Specify any planned assessment of metabias(es) (e.g., publication bias across studies and selective reporting within studies) Confdence in cumulative evidence 17 Describe how the strength of the body of evidence will be assessed (e.g., GRADE)

Data Collection Process.
For the included studies, the following parameters were extracted: author(s); year of publication; SARS-CoV-2 viral load in saliva; OPS, NPS, and/or sputum (expressed in C T value or copies/mL RNA); methods to detect viral load; saliva sampling; total cohort size; percentage of SARS-CoV-2 positive saliva; days of symptom onset; and salivary viral load in symptomatic and asymptomatic COVID-19 patients, if available. If information was missing, corresponding authors were contacted to complete the data. Firstly, the SARS-CoV-2 load (expressed in C T value or copies/mL RNA) in saliva was obtained, and secondly, the viral load in saliva was compared to OPS, NPS, or sputum. Finally, the diference in salivary viral load of symptomatic and asymptomatic COVID-19 patients was obtained.

Risk of Bias in Individual Studies.
Te potential risk of bias in the included studies was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies developed by NIH (National Heart, Lung, and Blood Institute) [36]. Tree authors performed the quality assessment independently. Based on the number of "Yes" answers, a rating of good (9-11), fair (5-8), or poor (≤4) was allocated to the individual study. Tis tool includes 14 questions which were answered by (Yes/No/Not applicable/Not reported/Cannot be determined), see Table 2. Diferences in quality rating were discussed by all reviewers (MF, FB, and ML) to reach a consensus.

Data Synthesis.
Data on SARS-CoV-2 salivary load were summarized and compared with SARS-CoV-2 load in OPS, NPS, and/or sputum. When ≥3 comparable studies were available, a meta-analysis was conducted using Review Manager (RevMan version 5.4, the Cochrane Collaboration, 2020), where appropriate, the mean (of viral C T value and viral copies/mL RNA) and standard deviations (SD) were derived. If the mean and SD were not reported, then they were derived from the sample size, median, interquartile range (IQR), and minimum and maximum values using an online calculator at https://www.math.hkbu.edu.hk/~tongt/ papers/median2mean.html.Random-efects. A model in RevMan 5.4 was selected to measure the standard mean diference for continuous outcome data with 95% confdence interval (CI). Forest plots were conducted to visualize characteristics of the selected studies; the standard mean diference of viral load in saliva was compared to OPS, NPS, and sputum and the heterogeneity between the studies (I 2 ). A random efects model was applied for moderate heterogeneity (>30%), otherwise the fxed efects model was applied. Te overall mean was obtained. P value <0.05 was considered as statistically signifcant.

Study Selection.
A total of 712 articles were retrieved through database search ( Figure 1). After duplicate removal, 259 articles were screened by the title and abstract and 147 articles were included for full-text reading after which 111 were excluded. Finally, a total of 37 papers were included. Tree additional articles were included by manual search.

Study Characteristics.
A total of 21 of the 37 selected studies reported the viral load as a mean or median C T value (Tables 3-5), while 16 studies reported the viral load in copies/mL RNA (Tables 6-9). Ten articles reported the viral load solely in saliva and 21 articles reported it in saliva compared with OPS, NPS, and/or sputum. Te remaining six studies reported the viral load in OPS [1,49,50,59,60] and sputum combined with saliva [7]. Five of the 31 studies that reported on salivary viral load collected unstimulated whole saliva (UWS) by drooling: the saliva was collected at the bottom of the mouth and then relieved into the collection device [12,31,[37][38][39]. Other studies reported saliva collection methods including spitting (three studies) [13,57,58], self-collection (eight studies) [11, 14, 33, 42-44, 47, 48], funnel (one study) [32], gargling (one study) [10], saliva stimulated by rubbing outside of the cheeks and then spitting (one study) [15], by coughing (two studies) [41,54], and by collecting naso-oropharyngeal saliva (two studies) [45,46]. One study purchased saliva from COVID-19 patients [51]. Seven studies did not report the saliva collection method; however, these studies were included because the viral loads were reported in all cases.
In 24 studies, the viral load dynamics of diferent respiratory tract samples was evaluated at the early phase of infection (frst week), while in fve studies, it was assessed in the second week of the infection. Te remaining eight studies did not report the days of symptom onset. Furthermore, fve studies included the viral load of saliva in symptomatic and asymptomatic COVID-19 patients; in four studies, the mean viral load was reported as C T value.

SARS-CoV-2 Load in Saliva.
Te mean SARS-CoV-2 load in saliva derived from 22 studies included 916 patients in total and showed mean C T values ranging from: 21.5 to 39.6 (Tables 3, 4, 6, and 7). Eleven studies included a total of 216 patients with a mean range of 1.91 × 10 1 to 5.69 × 10 11 copies/mL RNA (Tables 6 and 7).

SARS-CoV-2 Load in Saliva Compared with NPS.
A total of 13 studies were included for comparison of the standard mean diference in C T values of saliva and NPS ( Figure 2). No signifcant diferences were found in the mean viral load between saliva (overall mean: 26.4) and NPS (overall mean: 26.9 (P > 0.05). However, there was considerable heterogeneity between these studies (P < 0.00001; I 2 � 93%; 95% CI: −0.36-0.64), demonstrating that these data should be interpreted with caution but might be considered as a trend. Five studies compared the standard mean diference of the viral load given in copies/mL RNA in saliva and NPS ( Figure 3). No signifcant diferences were found in the mean viral load between saliva (overall mean: 1.80 × 10 22 ) and NPS (overall mean: 2.78 × 10 20 ) (P > 0.05), and moderate heterogeneity was observed across the studies (P � 0.03; I 2 � 63%; 95% CI: −0.47-0.59). Quality was rated based on the number of "Yes" answers out of 14 questions, a rating of good (9-11), fair (5-8), or poor (≤4). NA � not applicable, NR � not reported, ND � not detected, and CD � cannot be determined.

SARS-CoV-2 Load in Saliva Compared with OPS.
Four studies were included for comparison of the standard mean diference in C T values of saliva and OPS ( Figure 4). No signifcant diferences were found in the mean viral load between saliva (overall mean: 28.8) and OPS (overall mean: 30.5) (P > 0.05). Moderate heterogeneity was found between the studies (P � 0.19; I 2 � 36%; 95% CI: −0.88-0.13).

SARS-CoV-2 Load in Saliva Compared with Sputum.
Data from four published studies were selected to compare the mean C T values of saliva with sputum ( Figure 5). No signifcant diferences (P > 0.05) and no heterogeneity was found in the mean viral load between saliva (overall mean: 29.3) and sputum (overall mean: 28.8) (P � 0.88; I 2 � 0%; 95% CI: −0.65-0.50), demonstrating that these data are homogenous.

SARS-CoV-2 Load in Saliva of Symptomatic and
Asymptomatic COVID-19 Patients. A meta-analysis was conducted to explore the standard mean diference of SARS-CoV-2 load in saliva of symptomatic and asymptomatic COVID-19 patients. Data from four published studies were selected to compare the mean C T value of saliva in symptomatic and asymptomatic patients (Figure 6). Results indicate that no signifcant diferences were found in the mean viral load between symptomatic (overall mean: 26.06) and asymptomatic patients (overall mean: 25.7) (P > 0.05). However, a substantial heterogeneity was obtained between these studies (P � 0.03; I 2 � 66%; 95% CI: −0.63-0.37).

Risk of Bias Assessment.
Overall, 32 studies had a fair risk of bias (Table 2). Tree studies were deemed to have a low risk of bias and one study had a high risk of bias. Te overall rating in the quality of the studies was fair.

Discussion
Meta-analysis of 37 included articles revealed that the viral load of SARS-CoV-2 in saliva was comparable to that in NPS, OPS, and/or sputum. Data also disclosed that the viral                    in saliva; analysis of these values, however, revealed no statistically signifcant diferences [45]. Tough, interestingly, it has also been reported that the viral load in saliva peaks earlier, i.e., the frst week after infection, and declines less rapidly compared to NPS, suggesting a higher postinfection window of opportunity in saliva for screening and diagnostic purposes [66]. It is thought that the higher viral load and longevity of the virus in saliva may be due to a higher level of ACE2 receptors at various sites in the oral cavity (gingiva, shed epithelial cells in saliva, mucosa, tongue, hard and soft palate, and salivary glands) compared to the nasopharynx [17,19,[21][22][23][24][25]. Saliva has also been shown to be sensitive enough to detect the majority of viable infections compared to NPS with potential higher likelihood of viral transmission [66].
A considerable heterogeneity was obtained in the meta-analysis of viral load in saliva compared with NPS, which could be explained by the sample size of the studies. To exemplify, the study of Yee et al. (2021) and Teo et al. (2021) had the largest sample sizes: n � 127 and n � 209, respectively, whereas the sample sizes of other studies varied between 2 and 41. Furthermore, diferences in saliva collecting methods may contribute to the heterogeneity. For example, the study of Yee et al. (2021) used a diferent method for saliva collection compared to the other studies. Furthermore, the authors described that saliva was frst stimulated by gently rubbing the outside of the cheeks and subsequently by spitting without interference of coughed-up saliva. Potentially, this method could have stimulated minor salivary glands and parotid glands, secreting predominantly serous saliva potentially loaded with SARS-CoV-2 particles. Te saliva sampling methods of the other 11 studies were diverse: six studies reported self-collection [14, 42-44, 47, 48], one study used the so-called drooling method [12], two studies were instructed to collect naso-oropharyngeal saliva [45,46] and subsequently were asked to spit repeatedly in a sterile cup [45], one study reported coughed-up saliva from the throat [10] while two studies did not report the collection method at all [34,40]. Currently, there is a lack of a globally accepted and standardized saliva collection protocol for SARS-CoV-2 analysis. However, despite the diferent saliva collection methods, PCR primers, and conditions, the study set-ups are not likely to have a major infuence on the viral loads [67,68]. Te passive drooling technique is generally recommended as standard for saliva collection [69][70][71]. It is stated that this method provides the greatest sensitivity and allows collecting whole saliva excluding mucous secretions from the oropharynx and sputum [37]. It is an easy and safe technique that can be done with relative simple instructions. As this study revealed that the viral load is comparable in all sample types, we recommend the use of sampling unstimulated saliva, unless other techniques are preferred, e.g., for sake of efciency, logistic reasons, or standardization. To exemplify, for patients that are intubated and are not able to drool, it is suggested to pipette the saliva sample [70]. Another explanation for the heterogeneity could be that the viral load in saliva changed by food intake and by the circadian rhythm. Wyllie et al. (2020) and  found the highest viral load of 61.5% in the morning, compared to before lunch 23.1%, 3PM, before dinner 7.7%, and at bedtime 0%. Exact times of sampling, however, were not reported. Te relative high viral load in the morning may be due to overnight fasting and decreased salivary fow rate during sleep [72]. Consequently, it is, therefore, suggested to refrain from consumption of food and drinks in the morning prior to saliva collection [73]. Te same study showed that the salivary fow rate increased after food consumption, which may dilute or wash out the viral RNA [28,74,75]. Another factor causing heterogeneity might be the dilution of saliva samples after collection in viral transport medium (VTM). In line, some studies showed that collecting undiluted unstimulated saliva is preferable since the sensitivity and viral detection rates were higher than diluted unstimulated saliva. Tis processing method also showed no RNA degradation [10,15,33]. Most studies were found to have a fair risk of bias, largely due to not providing sample size calculation and power description, as well as not adjusting for potential confounding variables that might impact the outcome such as age and gender.
Meta-analysis from this study is in line with previous studies and demonstrated that no signifcant diferences were found in the viral load of saliva compared to sputum [43,[76][77][78][79]. Te viral load of sputum showed greater variation than saliva [78,80,81]. Tis could partly be related to the fact that the thick mucus from sputum hampers the viral RNA extraction [82]. It has also been observed that many patients are unable to produce enough sputum and coughs, making it an unsuitable method leading to decreased test sensitivity [77,83].  We found that the viral load in saliva was comparable to OPS as indicated by C T values. Tis fnding is in line with other studies [10,84]. In contrast, however, Moreno-Contreras et al. (2020) found that saliva had a signifcantly higher viral load compared to OPS, whereas OPS and NPS combined (NPS + OPS) were shown to have a comparable viral load with saliva, suggesting that saliva is a good alternative sampling matrix for NPS + OPS. Te reason for the diference between OPS and saliva viral load is unclear, but it is tempting to hypothesize that OPS was not sampled correctly due to the risks associated with this process. A total of 73.1% of NPS positive cases were negative in OPS [85], rendering it a less reliable specimen, as also reported by Khiabani et al. (2021).
Meta-analysis from the current study showed that the mean SARS-CoV-2 loads in saliva of symptomatic and asymptomatic COVID-19 patients are comparable as revealed by C T values and also shown by other authors [86][87][88]. Similar viral loads have been also found in other fuids (NPS, OPS, and sputum) [89,90]. A possible explanation for their comparable viral load could be the shedding of SARS-CoV-2 viral RNA originating from fragmented/ degraded genomes of dead viral particles within the oral epithelial cells which has been shed into the saliva of asymptomatic individuals. It has been reported that a high amount of viral RNA does not necessarily mean greater infectivity [89,91,92].
It has to be noted that in due course of the current study, new variants of SARS-CoV-2 emerged. Studies on the so-called Omicron variant (B.1.1.529) reported that the viral shedding rate is higher in saliva than in nasal samples [93][94][95]. It is shown that the salivary Omicron load peaks 1-2 days earlier than the nasal swabs detected by RT-PCR [93]. Marais et al. also concluded that saliva swabs performed better than midturbinate samples up to day 5 postinfection with positive percent agreement (PPA) of 96%. Individuals in the cohort study from Adamson et al. showed to develop symptoms within 2 days after frst positive saliva PCR test [93]. Even more, faster and more efcient infection rates have been found for the Omicron variant in the human bronchus compared to the previous SARS-CoV-2 variant, leading to symptoms such as loss of smell and taste which are, therefore, better detected in saliva compared to NPS [93,94,96]. Saliva antigen tests and RT-PCR, however, showed a declined sensitivity in Omicron infections after day 5 postinfection with an overall PPA (of RT-PCR) of 96% to approximately 50% [95]. Several studies conclude that saliva swabs are a promising alternative to NPS and midturbinate samples, especially early in infection [93][94][95]. It is, therefore, advised to use saliva samples as a diagnostic matrix for detecting the Omicron variant, instead of the currently used NPS. Many previous studies have also shown that the diagnostic performance of saliva tests has been successful in other viral infections, i.e., HIV [97][98][99]. More research is needed to reveal the diagnostic accuracy of saliva, especially in latestage of infection, for identifying the Omicron and possibly future variants of concern.

Limitations
Some data of the viral load (in C T values or copies/mL RNA), SD, and/or IQR were not available and, therefore, could not be included in the meta-analysis. Secondly, the fact that only four studies reported the C T value and SD of saliva from symptomatic and asymptomatic patients, provided only a small basis for comparison. Tirdly, in some studies, the methods of saliva collection were not reported in detail or at all. Also, saliva characteristics such as viscosity may have infuenced the SARS-CoV-2 detection. UWS has usually a mucous consistency, whereas stimulated saliva is relatively serous produced [100].

Conclusion
Tis systematic review revealed that SARS-CoV-2 load in saliva is comparable to OPS, NPS, and sputum. Saliva specimen can therefore be used as alternative for SARS-CoV-2 detection since it is noninvasive, convenient, safe, and therefore ideal for mass screening. In addition, it was found that the SARS-CoV-2 loads in saliva of asymptomatic and symptomatic COVID-19 patients were not signifcantly diferent.

Data Availability
Te data used to support the fndings of this study are available within the article. Tis is a review based on published data.

Conflicts of Interest
Te authors declare that they have no conficts of interest.